Articles | Volume 14, issue 7
The Cryosphere, 14, 2409–2428, 2020
The Cryosphere, 14, 2409–2428, 2020
Research article
27 Jul 2020
Research article | 27 Jul 2020

Statistical predictability of the Arctic sea ice volume anomaly: identifying predictors and optimal sampling locations

Leandro Ponsoni et al.

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Cited articles

Amélineau, F., Grémillet, D., Bonnet, D., Le Bot, T., and Fort, J.: Where to Forage in the Absence of Sea Ice? Bathymetry As a Key Factor for an Arctic Seabird, PLoS ONE, 11, e0157764,, 2016. a
Barnett, D. G.: Empirical orthogonal functions and the statistical predictability of sea ice extent, in: Sea Ice Processes and Models, edited by: Pritchard, R. S., Univ. Wash. Press, Seattle, 1980. a
Blanchard-Wrigglesworth, E. and Bitz, C.: Characteristics of Arctic Sea-Ice Thickness Variability in GCMs, J. Clim., 27, 8244–8258,, 2014. a
Brown, T. A., Galicia, M. P., Thiemann, G. W., Belt, S. T., Yurkowski, D. J., and Dyck, M. G.: High contributions of sea ice derived carbon in polar bear (Ursus maritimus) tissue, PLoS ONE, 13, e0191631,, 2016. a
Burgard, C. and Notz, D.: Drivers of Arctic Ocean warming in CMIP5 models, Geophys. Res. Let., 44, 4263–4271,, 2017. a
Short summary
The continuous melting of the Arctic sea ice observed in the last decades has a significant impact at global and regional scales. To understand the amplitude and consequences of this impact, the monitoring of the total sea ice volume is crucial. However, in situ monitoring in such a harsh environment is hard to perform and far too expensive. This study shows that four well-placed sampling locations are sufficient to explain about 70 % of the inter-annual changes in the pan-Arctic sea ice volume.